The optimisation of surveillance and detection systems comprised of specialised cameras is a well-known problem in the operations research literature. In these problems, the aim is to locate optimal camera sites so that their combined coverage with respect to some area of interest – called a cover zone – is maximised. The standard approach is to maximise cover with respect to a single cover zone, and to consider either cameras providing rotational (360°) cover, or cameras fixed to a specific direction and with visibility limited to within the camera's field-of-view. The Rhino Pride Foundation in South Africa required the optimisation of a camera surveillance system for a new protected area. Their coverage requirements were, however, beyond what has been previously encountered in the literature. Four covering objectives over three separate cover zones were to be maximised, while the system was to be optimised for rotational cover during the day, and some cameras would be required to be fixed towards a high-risk zone at night and limited to their field-of-view. A novel multi-attribute genetic algorithm based on the popular NSGA-II was developed for this purpose. Various solutions were provided to and considered by the Rhino Pride Foundation, and the final selected solution resulted in camera site locations providing high-quality cover with respect to all the covering objectives, while requiring fewer cameras than initially expected – resulting in significant cost savings and reduced future maintenance and upgrade requirements. The solution approach presented here may be applied to other site-selection problems with similar coverage requirements, including military radar and weapon systems, and wildfire detection systems.

由特种摄像机组成的监视和检测系统的优化是运筹学文献中的一个众所周知的问题。在这些问题中，目标是找到最佳的摄像头位置，以使它们在某些感兴趣区域（称为覆盖区）的组合覆盖范围最大化。标准方法是针对单个覆盖区域最大化覆盖范围，并考虑提供可旋转（360°）覆盖的摄像机，或考虑固定在特定方向且可见度仅限于摄像机视野内的摄像机。南非的Rhino Pride基金会要求针对新的保护区优化摄像机监控系统。但是，它们的覆盖范围要求超出了文献中先前遇到的范围。要在三个单独的覆盖区域上最大化四个覆盖物镜，同时还要对该系统进行白天轮转覆盖的优化，并且某些摄像头需要在夜间固定在高风险区域，并且仅限于其野外使用。看法。为此，开发了一种基于流行的NSGA-II的新颖的多属性遗传算法。Rhino Pride基金会提供了各种解决方案并考虑了这些解决方案，最终选择的解决方案使摄像头的位置相对于所有覆盖物镜都能提供高质量的覆盖，同时所需的摄像头比最初预期的要少，从而显着节省了成本，并且减少了将来的维护和升级要求。